Automatic induction of lexical features

This thesis concerns artificially intelligent natural language processing systems that are capable of learning the properties of lexical items (properties like verbal valency or inflectional class membership) autonomously while they are fulfilling their tasks for which they have been deployed in the first place. Many of these tasks require a deep analysis of language input, which can be characterized as a mapping of utterances in a given input C to a set S of linguistically motivated structures with the help of linguistic information encoded in a grammar G and a lexicon L: G + L + C → S (1) The idea that underlies intelligent lexical acquisition systems is to modify this schematic formula in such a way that the system is able to exploit the information encoded in S to create a new, improved version of the lexicon: G + L + S → L' (2) Moreover, the thesis claims that a system can only be considered intelligent if it does not just make maximum usage of the learning opportunities in C, but if it is also able to revise falsely acquired lexical knowledge. So, one of the central elements in this work is the formulation of a couple of criteria for intelligent lexical acquisition systems subsumed under one paradigm: the Learn-Alpha design rule. The thesis describes the design and quality of a prototype for such a system, whose acquisition components have been developed from scratch and built on top of one of the state-of-the-art Head-driven Phrase Structure Grammar (HPSG) processing systems. The quality of this prototype is investigated in a series of experiments, in which the system is fed with extracts of a large English corpus. While the idea of using machine-readable language input to automatically acquire lexical knowledge is not new, we are not aware of a system that fulfills Learn-Alpha and is able to deal with large corpora. To instance four major challenges of constructing such a system, it should be mentioned that a) the high number of possible structural descriptions caused by highly underspeci ed lexical entries demands for a parser with a very effective ambiguity management system, b) the automatic construction of concise lexical entries out of a bulk of observed lexical facts requires a special technique of data alignment, c) the reliability of these entries depends on the system's decision on whether it has seen 'enough' input and d) general properties of language might render some lexical features indeterminable if the system tries to acquire them with a too high precision. The cornerstone of this dissertation is the motivation and development of a general theory of automatic lexical acquisition that is applicable to every language and independent of any particular theory of grammar or lexicon. This work is divided into five chapters. The introductory chapter first contrasts three different and mutually incompatible approaches to (artificial) lexical acquisition: cue-based queries, head-lexicalized probabilistic context free grammars and learning by unification. Then the postulation of the Learn-Alpha design rule is presented. The second chapter outlines the theory that underlies Learn-Alpha and exposes all the related notions and concepts required for a proper understanding of artificial lexical acquisition. Chapter 3 develops the prototyped acquisition method, called ANALYZE-LEARN-REDUCE, a framework which implements Learn-Alpha. The fourth chapter presents the design and results of a bootstrapping experiment conducted on this prototype: lexeme detection, learning of verbal valency, categorization into nominal count/mass classes, selection of prepositions and sentential complements, among others. The thesis concludes with a review of the conclusions and motivation for further improvements as well as proposals for future research on the automatic induction of lexical features.

Vaccination-induced functional competence of circulating human tumor-specific CD8 T-cells

T-cells specific for foreign (e.g., viral) antigens can give rise to strong protective immune responses, whereas self/tumor antigen-specific T-cells are thought to be less powerful. However, synthetic T-cell vaccines composed of Melan-A/MART-1 peptide, CpG and IFA can induce high frequencies of tumor-specific CD8 T-cells in PBMC of melanoma patients. Here we analyzed the functionality of these T-cells directly ex vivo, by multiparameter flow cytometry. The production of multiple cytokines (IFNγ, TNFα, IL-2) and upregulation of LAMP-1 (CD107a) by tumor (Melan-A/MART-1) specific T-cells was comparable to virus (EBV-BMLF1) specific CD8 T-cells. Furthermore, phosphorylation of STAT1, STAT5 and ERK1/2, and expression of CD3 zeta chain were similar in tumor- and virus-specific T-cells, demonstrating functional signaling pathways. Interestingly, high frequencies of functionally competent T-cells were induced irrespective of patient's age or gender. Finally, CD8 T-cell function correlated with disease-free survival. However, this result is preliminary since the study was a Phase I clinical trial. We conclude that human tumor-specific CD8 T-cells can reach functional competence in vivo, encouraging further development and Phase III trials assessing the clinical efficacy of robust vaccination strategies.

Lexical Development in Adult Beginning Second Language Learners

This research tests the hypothesis that knowledge of derivational morphology facilitates vocabulary acquisition in beginning adult second language learners. Participants were mono-lingual English-speaking college students aged 18 years and older enrolled inintroductory Spanish courses. Knowledge of Spanish derivational morphology was tested through the use of a forced-choice translation task. Spanish lexical knowledge was measured by a translation task using direct translation (English word) primes and conceptual (picture) primes. A 2x2x2 mixed factor ANOVA examined the relationships between morphological knowledge (strong, moderate), error type (form-based, conceptual), and prime type (direct translation, picture). The results are consistent with the existence of a relationship between knowledge of derivational morphology andacquisition of second language vocabulary. Participants made more conceptually-based errors than form-based errors F (1,22)=7.744, p=.011. This result is consistent with Clahsen & Felser’s (2006) and Ullman’s (2004) models of second language processing. Additionally, participants with Strong morphological knowledge made fewer errors onthe lexical knowledge task than participants with Moderate morphological knowledge t(23)=-2.656, p=.014. I suggest future directions to clarify the relationship between morphological knowledge and lexical development in adult second language learners.

Board examination for anatomical pathology in Switzerland: two intense days to verify professional competence

About 15 years ago, the Swiss Society of Pathology has developed and implemented a board examination in anatomical pathology. We describe herein the contents covered by this 2-day exam (autopsy pathology, cytology, histopathology, molecular pathology, and basic knowledge about mechanisms of disease) and its exact modalities, sketch a brief history of the exam, and finish with a concise discussion about the possible objectives and putative benefits weighed against the hardship that it imposes on the candidates.

Competence of Long-Term Care Residence to Participate in Decisions About Their Medical Care: A Brief, Objective Assessment

Data from 50 residents of a long-term care facility were used to examine the extent to which performance on a brief, objective inventory could predict a clinical psychologist's evaluation of competence to participate in decisions about medical care. Results indicate that the competence to participate in medical decisions of two-thirds of the residents could be accurately assessed using scores on a mental status instrument and two vignette-based measures of medical decision-making. These procedures could enable nursing home staff to objectively assess the competence of residents to participate in important decisions about their medical care.

A Computational Model for Processing Lexical Information"

The group analysed some syntactic and phonological phenomena that presuppose the existence of interrelated components within the lexicon, which motivate the assumption that there are some sublexicons within the global lexicon of a speaker. This result is confirmed by experimental findings in neurolinguistics. Hungarian speaking agrammatic aphasics were tested in several ways, the results showing that the sublexicon of closed-class lexical items provides a highly automated complex device for processing surface sentence structure. Analysing Hungarian ellipsis data from a semantic-syntactic aspect, the group established that the lexicon is best conceived of being as split into at least two main sublexicons: the store of semantic-syntactic feature bundles and a separate store of sound forms. On this basis they proposed a format for representing open-class lexical items whose meanings are connected via certain semantic relations. They also proposed a new classification of verbs to account for the contribution of the aspectual reading of the sentence depending on the referential type of the argument, and a new account of the syntactic and semantic behaviour of aspectual prefixes. The partitioned sets of lexical items are sublexicons on phonological grounds. These sublexicons differ in terms of phonotactic grammaticality. The degrees of phonotactic grammaticality are tied up with the problem of psychological reality, of how many degrees of this native speakers are sensitive to. The group developed a hierarchical construction network as an extension of the original General Inheritance Network formalism and this framework was then used as a platform for the implementation of the grammar fragments.